package com.heima.common.aliyun;

import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONArray;
import com.alibaba.fastjson.JSONObject;
import com.aliyuncs.DefaultAcsClient;
import com.aliyuncs.IAcsClient;
import com.aliyuncs.green.model.v20180509.ImageSyncScanRequest;
import com.aliyuncs.http.FormatType;
import com.aliyuncs.http.HttpResponse;
import com.aliyuncs.http.MethodType;
import com.aliyuncs.http.ProtocolType;
import com.aliyuncs.profile.DefaultProfile;
import com.aliyuncs.profile.IClientProfile;
import com.heima.common.aliyun.util.ClientUploader;
import lombok.Data;
import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.stereotype.Component;

import java.util.*;

@Data
@Component
@ConfigurationProperties(prefix = "aliyun.oss")
public class GreenImageScan {

    private String accessKeyId;
    private String accessKeySecret;
    private String scenes;

    public Map imageScan(List<byte[]> imageList) throws Exception{
        IClientProfile profile = DefaultProfile
                .getProfile("cn-shanghai",accessKeyId,accessKeySecret);
        DefaultProfile
                .addEndpoint("cn-shanghai","cn-shanghai","Green","green.cn-shanghai.aliyuncs.com");
        IAcsClient client = new DefaultAcsClient(profile);
        ImageSyncScanRequest imageSyncScanRequest = new ImageSyncScanRequest();
        // 指定api返回格式
        imageSyncScanRequest.setAcceptFormat(FormatType.JSON);
        // 指定请求方法
        imageSyncScanRequest.setMethod(MethodType.POST);
        imageSyncScanRequest.setEncoding("utf-8");
        // 支持http和https
        imageSyncScanRequest.setProtocol(ProtocolType.HTTP);
        JSONObject httpBody = new JSONObject();
        /**
         * 设置要检测的场景，计费是按照该处传递的场景进行
         * 一次请求中可以同时检测多张图片，每张图片可以同时检测多个风险场景，计费按照场景计算
         * 例如：检测2张图片，场景传递porn、terrorism,计费会按照2张图片鉴黄，2张图片暴恐检测计费
         * porn:porn表示色情场景检测
         */
        httpBody.put("scenes", Arrays.asList(scenes.split(",")));
        /**
         * 如果您要检测的文件存于本地服务器上，可以通过下述代码片生成url
         * 再将返回的url作为图片地址传递到服务器进行检测
         */
        /**
         * 设置待检测图片， 一张图片一个task
         * 多张图片同时检测时，处理的时间由最后一个处理完的图片决定
         * 通常情况下批量检测的平均rt比单张检测的要长，一次批量提交的图片数越多，rt被拉长的概率越高
         * 这里以单张图片检测作为示例，如果是批量图片检测，请自行构建多个task
         */
        ClientUploader clientUploader = ClientUploader.getImageClientUpload(profile,false);
        String url = null;
        List<JSONObject> urlList = new ArrayList<>();
        for (byte[] bytes : imageList){
            url = clientUploader.uploadBytes(bytes);
            JSONObject task = new JSONObject();
            task.put("dataId", UUID.randomUUID().toString());
            // 设置图片链接为上传后的url
            task.put("url",url);
            task.put("time",new Date());
            urlList.add(task);
        }
        httpBody.put("tasks",urlList);
        imageSyncScanRequest.setHttpContent(org.apache.commons.codec.binary.StringUtils.getBytesUtf8(httpBody.toJSONString()),
                "UTF-8",FormatType.JSON);
        /**
         * 请设置超时时间，服务端全链路处理超时时间为20秒，请做相应设置
         * 如果您设置的ReadTimeout小于服务端处理的时间，程序中会获得一个read timeout异常
         */
        imageSyncScanRequest.setConnectTimeout(6000);
        imageSyncScanRequest.setReadTimeout(20000);
        HttpResponse httpResponse = null;
        try {
            httpResponse = client.doAction(imageSyncScanRequest);
        }catch (Exception e){
            e.printStackTrace();
        }

        Map<String,String> resultMap = new HashMap<>();

        // 服务端接收到请求，并完成处理返回的结果
        if (httpResponse != null && httpResponse.isSuccess()){
            JSONObject scrResponse = JSON.parseObject(org.apache.commons.codec.binary.StringUtils.newStringUtf8(httpResponse.getHttpContent()));
            System.out.println(JSON.toJSONString(scrResponse,true));
            int requestCode = scrResponse.getIntValue("code");
            // 每一张图片的检测结果
            JSONArray taskResults = scrResponse.getJSONArray("data");
            if (200 == requestCode){
                for (Object taskResult : taskResults){
                    // 单张图片的处理结果
                    int taskCode = ((JSONObject) taskResult).getIntValue("code");
                    // 图片要检测的场景的处理结果，如果是多个场景，则会有每个场景的结果
                    JSONArray sceneResults = ((JSONObject) taskResult).getJSONArray("result");
                    if (200 == taskCode){
                        for (Object sceneResult : sceneResults){
                            String scene = ((JSONObject) sceneResult).getString("scene");
                            String label = ((JSONObject) sceneResult).getString("label");
                            String suggestion = ((JSONObject) sceneResult).getString("suggestion");
                            // 根据scene和suggetion做相关处理
                            // do something
                            System.out.println("scene = [" + scene + "]");
                            System.out.println("suggestion = [" + suggestion + "]");
                            System.out.println("label = [" + label + "]");
                            if (!suggestion.equals("pass")){
                                resultMap.put("suggestion",suggestion);
                                resultMap.put("label",label);
                                return resultMap;
                            }
                        }
                    }else {
                        // 单张图片处理失败，原因视具体的情况详细分析
                        System.out.println("task process fail. task response:" + JSON.toJSONString(taskResult));
                        return null;
                    }
                }
                resultMap.put("suggestion","pass");
                return resultMap;
            }else {
                /**
                 * 表明请求整体处理失败，原因视具体的情况详细分析
                 */
                System.out.println("the whole image scan request failed. response:" + JSON.toJSONString(scrResponse));
                return null;
            }
        }
        return null;
    }

    public Map checkUrl(List<String> urls) throws Exception{
        IClientProfile profile = DefaultProfile
                .getProfile("cn-shanghai",accessKeyId,accessKeySecret);
        DefaultProfile
                .addEndpoint("cn-shanghai","cn-shanghai","Green","green.cn-shanghai.aliyuncs.com");
        IAcsClient client = new DefaultAcsClient(profile);
        ImageSyncScanRequest imageSyncScanRequest = new ImageSyncScanRequest();
        // 指定api返回格式
        imageSyncScanRequest.setAcceptFormat(FormatType.JSON);
        // 指定请求方法
        imageSyncScanRequest.setMethod(MethodType.POST);
        imageSyncScanRequest.setEncoding("utf-8");
        // 支持http和https
        imageSyncScanRequest.setProtocol(ProtocolType.HTTP);
        JSONObject httpBody = new JSONObject();
        /**
         * 设置要检测的风险场景，计费依据此处传递的场景计算
         * 一次请求中可以同时检测多张图片，每张图片可以同时检测多个风险场景，计费按照场景计算
         * 例如：检测2张图片，场景传递porn和terrorism,计费会按照2张图片鉴黄，2张图片暴恐检测计算
         * porn: 表示鉴黄场景
         */
        httpBody.put("scenes", Arrays.asList(scenes.split(",")));
        /**
         * 设置待检测图片， 一张图片对应一个task
         * 多张图片同时检测时，处理的时间由最后一个处理完的图片决定
         * 通常情况下批量检测的平均rt比单张检测的要长，一次批量提交的图片数越多，响应时间被拉长的概率越高
         * 这里以单张图片检测作为示例，如果是批量图片检测，请自行构建多个task
         */
        List<JSONObject> tasks = new ArrayList<>();
        // 设置图片链接
        for (String url : urls){
            JSONObject task = new JSONObject();
            task.put("dataId", UUID.randomUUID().toString());
            task.put("url",url);
            task.put("time",new Date());
            tasks.add(task);
        }
        httpBody.put("tasks",tasks);
        imageSyncScanRequest.setHttpContent(org.apache.commons.codec.binary.StringUtils.getBytesUtf8(httpBody.toJSONString()),
                "UTF-8",FormatType.JSON);
        /**
         * 请设置超时时间，服务端全链路处理超时时间为10秒，请做相应设置
         * 如果您设置的ReadTimeout小于服务端处理的时间，程序中会获得一个read timeout异常
         */
        imageSyncScanRequest.setConnectTimeout(3000);
        imageSyncScanRequest.setReadTimeout(10000);
        HttpResponse httpResponse = null;
        try {
            httpResponse = client.doAction(imageSyncScanRequest);
        }catch (Exception e){
            e.printStackTrace();
        }

        Map<String,String> resultMap = new HashMap<>();

        // 服务端接收到请求，并完成处理返回的结果
        if (httpResponse != null && httpResponse.isSuccess()){
            JSONObject scrResponse = JSON.parseObject(org.apache.commons.codec.binary.StringUtils.newStringUtf8(httpResponse.getHttpContent()));
            System.out.println(JSON.toJSONString(scrResponse,true));
            int requestCode = scrResponse.getIntValue("code");
            // 每一张图片的检测结果
            JSONArray taskResults = scrResponse.getJSONArray("data");
            if (200 == requestCode){
                for (Object taskResult : taskResults){
                    // 单张图片的处理结果
                    int taskCode = ((JSONObject) taskResult).getIntValue("code");
                    // 图片要检测的场景的处理结果，如果是多个场景，则会有每个场景的结果
                    JSONArray sceneResults = ((JSONObject) taskResult).getJSONArray("results");
                    if (200 == taskCode){
                        for (Object sceneResult : sceneResults){
                            String scene = ((JSONObject) sceneResult).getString("scene");
                            String suggestion = ((JSONObject) sceneResult).getString("suggestion");
                            String label = ((JSONObject) sceneResult).getString("label");
                            // 根据scene和suggetion做相关处理
                            // do something
                            System.out.println("scene = [" + scene + "]");
                            System.out.println("suggestion = [" + suggestion + "]");
                            System.out.println("label = [" + label + "]");
                            if (!suggestion.equals("pass")){
                                resultMap.put("suggestion",suggestion);
                                resultMap.put("label",label);
                                return resultMap;
                            }
                        }
                    }else {
                        // 单张图片处理失败，原因视具体的情况详细分析
                        System.out.println("task process fail. task response:" + JSON.toJSONString(taskResult));
                        return null;
                    }
                }
                resultMap.put("suggestion","pass");
                return resultMap;
            }else {
                /**
                 * 表明请求整体处理失败，原因视具体的情况详细分析
                 */
                System.out.println("the whole image scan request failed. response:" + JSON.toJSONString(scrResponse));
                return null;
            }
        }
        return null;
    }

}
